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How Shippo balances positive experiences with unrivaled fraud protection
Technology Category
- Analytics & Modeling - Machine Learning
- Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
- E-Commerce
- Retail
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Fraud Detection
Services
- Software Design & Engineering Services
The Challenge
Shippo, a B2B shipping API provider, was facing a significant challenge with fraud. The company's business model, which allows users to create multiple shipping labels before having to pay, made it a target for fraudsters. The majority of the fraud fell into two categories: users who sign up with a fake email address and use a stolen credit card number, and users who create labels, hit the threshold, and then create a new account to avoid paying their invoices. In both cases, Shippo lost money – either from chargebacks from the accounts with stolen credit card numbers or lost revenue from the unpaid invoices. The company needed a solution that could preemptively identify account abuse and prevent users with stolen credentials from purchasing.
About The Customer
Shippo is a B2B shipping API that empowers businesses to ship orders through a global network of carriers. Founded in 2013, Shippo’s users include platforms, marketplaces, warehouses, and e-commerce businesses. Through Shippo, a business can easily print shipping labels and track orders. The company is focused on ensuring a positive business experience. In order to keep the flow as seamless as possible, Shippo doesn’t charge for individual shipping labels. Rather, every user is only invoiced after they exceed a certain order threshold. To sign up for Shippo, a user just needs to provide a credit card number – that won’t get charged until that first invoice is sent – and email address.
The Solution
Shippo turned to Sift to solve its fraud problem. The company was able to integrate with Sift in just a few hours, and the whole process was smooth and relatively effortless. Shippo began by sending Sift as much historical data as possible and relying on the machine learning technology to make sense of this dense information. Using Sift, Shippo could quickly separate out suspicious users from legitimate ones, and focus their energies on validating accounts and orders. Sift effectively caught fraudsters and was particularly valuable for identifying bad users at the account-creation stage. Shippo no longer had to wait until they saw a chargeback or a pile-up of invoices before spotting malicious users.
Operational Impact
Quantitative Benefit
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